{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/N/project/suicide_study/pnas_replication/results/log/logit_5.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}18 Aug 2020, 08:58:48
{txt}
{com}. 
. if ("`model'" == "logit"){c -(}
.         use "${c -(}home_dir{c )-}/data/processed/suicide_reg_v1_raw.dta", clear
. {c )-}
{txt}
{com}. 
. if ("`model'" == "mi") {c -(}
.         use "${c -(}home_dir{c )-}/data/processed/suicide_reg_v1_imputed_M10.dta", clear  
. {c )-}
{txt}
{com}. 
. * for now, we use the following simple survey weights 
. if ("`model'" == "mi") {c -(}
.         mi svyset `geo_type' [pw=ObsWgt0] 
. {c )-}
{txt}
{com}. else {c -(}
.         svyset `geo_type' [pw=ObsWgt0]  

      {txt}pweight:{col 16}{res}ObsWgt0
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}{res}county
        {txt}FPC 1:{col 16}<zero>
{p2colreset}{...}
{com}. {c )-}
{txt}
{com}. 
. * margins for each category
. program margin_interact 
{txt}  1{com}.         args X Y k model
{txt}  2{com}.         sum `X', d 
{txt}  3{com}.         local gap = (`r(max)' - `r(min)') / `k' 
{txt}  4{com}.         if ("`model'" == "logit") {c -(}
{txt}  5{com}.                 margin `Y', at(`X' = (`r(min)' (`gap') `r(max)')) predict(pr)
{txt}  6{com}.         {c )-} 
{txt}  7{com}.         else if ("`model'" == "mi") {c -(}
{txt}  8{com}.                 mimrgns `Y', at(`X' = (`r(min)' (`gap') `r(max)')) predict(pr)
{txt}  9{com}.         {c )-}       
{txt} 10{com}. end 
{txt}
{com}. 
. program mchange_mi
{txt}  1{com}.         args X k model
{txt}  2{com}.         if ("`model'" == "logit") {c -(}
{txt}  3{com}. 
.                 if ("`k'" == "continuous") {c -(}
{txt}  4{com}.                         sum `X' if e(sample), d 
{txt}  5{com}.                         margin, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt}  6{com}.                         mlincom  2 - 1, decimal(7) stat(all)    
{txt}  7{com}.                 {c )-} 
{txt}  8{com}.                 else if ("`k'" == "binary") {c -(}
{txt}  9{com}.                         sum `X' if e(sample), d 
{txt} 10{com}.                         margin, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt} 11{com}.                         mlincom  2 - 1, decimal(7) stat(all)
{txt} 12{com}.                 {c )-} 
{txt} 13{com}.                 else if ("`k'" == "categorical") {c -(}
{txt} 14{com}.                         margin `X' if e(sample)==1 , at() pwcompare predict(pr) 
{txt} 15{com}.                 {c )-}
{txt} 16{com}.         {c )-}
{txt} 17{com}. 
.         else if ("`model'" == "mi") {c -(}
{txt} 18{com}. 
.                 if ("`k'" == "continuous") {c -(}
{txt} 19{com}.                         sum `X' , d 
{txt} 20{com}.                         mimrgns, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt} 21{com}.                         mlincom  2 - 1, decimal(7) stat(all)
{txt} 22{com}.                 {c )-} 
{txt} 23{com}.                 else if ("`k'" == "binary") {c -(}
{txt} 24{com}.                         sum `X' , d 
{txt} 25{com}.                         mimrgns, at(`X' = (`r(min)' `r(max)')) post predict(pr)
{txt} 26{com}.                         mlincom  2 - 1, decimal(7) stat(all)
{txt} 27{com}.                 {c )-} 
{txt} 28{com}.                 else if ("`k'" == "categorical") {c -(}
{txt} 29{com}.                         mimrgns `X' , at()   pwcompare predict(pr)      
{txt} 30{com}.                 {c )-}
{txt} 31{com}.         {c )-}
{txt} 32{com}. end
{txt}
{com}. 
. * create some dummy codings
. tab Race5, gen(race5_nh)

      {txt}Race5 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}  9,802,895       79.53       79.53
{txt}          2 {c |}{res}  1,330,104       10.79       90.32
{txt}          3 {c |}{res}    260,664        2.11       92.44
{txt}          4 {c |}{res}    250,301        2.03       94.47
{txt}          5 {c |}{res}    681,739        5.53      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res} 12,325,703      100.00
{txt}
{com}.         rename race5_nh1 White_nh 
{res}{txt}
{com}.         rename race5_nh2 Black_nh 
{res}{txt}
{com}.         rename race5_nh3 AIAN_nh 
{res}{txt}
{com}.         rename race5_nh4 AsPI_nh 
{res}{txt}
{com}.         rename race5_nh5 Hispanic
{res}{txt}
{com}. 
. tab MarStat5, gen(ms)

   {txt}MarStat5 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}  6,880,735       55.83       55.83
{txt}          2 {c |}{res}    924,215        7.50       63.32
{txt}          3 {c |}{res}  1,265,861       10.27       73.60
{txt}          4 {c |}{res}    237,203        1.92       75.52
{txt}          5 {c |}{res}  3,017,228       24.48      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res} 12,325,242      100.00
{txt}
{com}.         rename ms1 Marrd5
{res}{txt}
{com}.         rename ms2 Widow5
{res}{txt}
{com}.         rename ms3 Divor5
{res}{txt}
{com}.         rename ms4 Separ5
{res}{txt}
{com}.         rename ms5 NvMar5
{res}{txt}
{com}. 
. tab AgeGrp4, gen(ag) 

    {txt}AgeGrp4 {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}  1,930,142       15.66       15.66
{txt}          2 {c |}{res}  3,549,392       28.80       44.46
{txt}          3 {c |}{res}  4,304,660       34.92       79.38
{txt}          4 {c |}{res}  2,541,509       20.62      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res} 12,325,703      100.00
{txt}
{com}.         rename ag1 Age_15_24
{res}{txt}
{com}.         rename ag2 Age_25_44
{res}{txt}
{com}.         rename ag3 Age_45_64
{res}{txt}
{com}.         rename ag4 Age_65_Up
{res}{txt}
{com}. 
. destring St, replace 
{txt}St: all characters numeric; {res}replaced {txt}as {res}byte
{txt}(16685 missing values generated)
{res}{txt}
{com}. 
. * set-up equations
. local religion Rat_GC_ProE Rat_GC_ProM Rat_GC_ProB Rat_GC_Cath Rat_GC_Jew Rat_GC_Oth
{txt}
{com}. local contextual_control Rat_Poverty Rat_Mig_Cum Pop_Den
{txt}
{com}. 
. local religion Rat_GC_ProE Rat_GC_ProM Rat_GC_ProB Rat_GC_Jew Rat_GC_Oth
{txt}
{com}. local contextual_control Rat_Poverty Rat_Mig_Cum Pop_Den
{txt}
{com}. 
. local demographics_raw i.Female c.RAT_Female i.AgeGrp4 c.RAT_AgeGrp4_2 c.RAT_AgeGrp4_3 c.RAT_AgeGrp4_4 i.Race5 c.RAT_Race5_2 c.RAT_Race5_3 c.RAT_Race5_4 c.RAT_Race5_5 i.BornUSA c.RAT_BornUSA i.MarStat5 c.RAT_MarStat5_2 c.RAT_MarStat5_3 c.RAT_MarStat5_4 c.RAT_MarStat5_5
{txt}
{com}. local demographics_same i.Female c.std_same_prop_Sex i.AgeGrp4 c.std_same_prop_AgeGrp4 i.Race5 c.std_same_prop_Race5 i.BornUSA c.std_same_prop_BornUSA i.MarStat5 c.std_same_prop_MarStat5 
{txt}
{com}. local demographics_inter i.Female##c.std_same_prop_Sex i.AgeGrp4##c.std_same_prop_AgeGrp4 i.Race5##c.std_same_prop_Race5 i.BornUSA##c.std_same_prop_BornUSA i.MarStat5##c.std_same_prop_MarStat5
{txt}
{com}. 
. 
. if (`model_version' == 1){c -(}
.         local model_eq i.Year `demographics_raw' `contextual_control' `religion' 
.         local margin_demographics Female RAT_Female AgeGrp4 RAT_AgeGrp4_2 RAT_AgeGrp4_3 RAT_AgeGrp4_4 Race5 RAT_Race5_2 RAT_Race5_3 RAT_Race5_4 RAT_Race5_5 BornUSA RAT_BornUSA MarStat5 RAT_MarStat5_2 RAT_MarStat5_3 RAT_MarStat5_4 RAT_MarStat5_5 
. {c )-}
{txt}
{com}. if (`model_version' == 2){c -(}
.         local model_eq i.Year `demographics_raw' `contextual_control' `religion' i.UnEmpl c.RAT_UnEmpl i.PhysProb c.RAT_PhysProb
.         local margin_demographics Female RAT_Female AgeGrp4 RAT_AgeGrp4_2 RAT_AgeGrp4_3 RAT_AgeGrp4_4 Race5 RAT_Race5_2 RAT_Race5_3 RAT_Race5_4 RAT_Race5_5 BornUSA RAT_BornUSA MarStat5 RAT_MarStat5_2 RAT_MarStat5_3 RAT_MarStat5_4 RAT_MarStat5_5 UnEmpl RAT_UnEmpl PhysProb RAT_PhysProb
. {c )-}
{txt}
{com}. if (`model_version' == 3){c -(}
.         local model_eq i.Year `demographics_same' `contextual_control' `religion' 
.         local margin_demographics Female std_same_prop_Sex AgeGrp4 std_same_prop_AgeGrp4 Race5 std_same_prop_Race5 BornUSA std_same_prop_BornUSA MarStat5 std_same_prop_MarStat5 
. {c )-}
{txt}
{com}. if (`model_version' == 4){c -(}
.         local model_eq i.Year `demographics_same' `contextual_control' `religion' i.UnEmpl c.std_same_prop_UnEmpl i.PhysProb c.std_same_prop_PhysProb
.         local margin_demographics Female std_same_prop_Sex AgeGrp4 std_same_prop_AgeGrp4 Race5 std_same_prop_Race5 BornUSA std_same_prop_BornUSA MarStat5 std_same_prop_MarStat5 UnEmpl std_same_prop_UnEmpl PhysProb std_same_prop_PhysProb
. {c )-}
{txt}
{com}. if (`model_version' == 5){c -(}
.         local model_eq i.Year `demographics_inter' `contextual_control' `religion' 
. {c )-}
{txt}
{com}. if (`model_version' == 6){c -(}
.         local model_eq i.Year `demographics_inter' `contextual_control' `religion' i.UnEmpl##c.std_same_prop_UnEmpl i.PhysProb##c.std_same_prop_PhysProb
. {c )-}       
{txt}
{com}. * test how long it would take.
. * mi estimate: svy: mean Suic 
. * local demographics i.Female c.RAT_Female i.AgeGrp4 c.RAT_AgeGrp4_2 c.RAT_AgeGrp4_3 c.RAT_AgeGrp4_4 i.Race5 c.RAT_Race5_2 c.RAT_Race5_3 c.RAT_Race5_4 c.RAT_Race5_5 i.BornUSA c.RAT_BornUSA i.MarStat5 c.RAT_MarStat5_2 c.RAT_MarStat5_3 c.RAT_MarStat5_4 c.RAT_MarStat5_5
. * mi estimate: svy: logit Suic i.St `demographics' UnEmpl RAT_UnEmpl PhysProb RAT_PhysProb
. 
. * main effects : margins
. if ("`model'" == "mi"){c -(}
. 
.         mi estimate: svy: logit Suic i.St `model_eq', or 
.         estimates store m1 
. 
.         if (`model_version' <= 4){c -(}
.                 estimates restore m1
.                 mchange_mi Female "binary" "mi"
.                 estimates restore m1
.                 mchange_mi AgeGrp4 "categorical" "mi"
.                 estimates restore m1
.                 mchange_mi Race5 "categorical" "mi"
.                 estimates restore m1
.                 mchange_mi BornUSA "binary" "mi"
.                 estimates restore m1
.                 mchange_mi MarStat5 "categorical" "mi"
.                 
.                 if (`model_version' == 1 | `model_version' == 2) {c -(}
.                         estimates restore m1
.                         mchange_mi RAT_Female "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_AgeGrp4_2 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_AgeGrp4_3 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_AgeGrp4_4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_2 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_3 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_Race5_5 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_BornUSA "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_2 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_3 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_MarStat5_5 "continuous" "mi"
.                 {c )-}
.                 if (`model_version' == 3 | `model_version' == 4) {c -(}
.                         estimates restore m1
.                         mchange_mi std_same_prop_Sex "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_AgeGrp4 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_Race5 "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_BornUSA "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_MarStat5 "continuous" "mi"
.                 {c )-}
.         
.                 if (`model_version' == 2 | `model_version' == 4){c -(}
.                         estimates restore m1
.                         mchange_mi UnEmpl "categorical" "mi"
.                         estimates restore m1
.                         mchange_mi PhysProb "categorical" "mi"
.                 {c )-}
.         
.                 if (`model_version' == 2){c -(}
.                         estimates restore m1
.                         mchange_mi RAT_UnEmpl "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi RAT_PhysProb "continuous" "mi"
.                 {c )-}
.                 if (`model_version' == 4){c -(}
.                         estimates restore m1
.                         mchange_mi std_same_prop_UnEmpl "continuous" "mi"
.                         estimates restore m1
.                         mchange_mi std_same_prop_PhysProb "continuous" "mi"
.                 {c )-}               
.         {c )-}
. {c )-}
{txt}
{com}. 
. if ("`model'" == "logit"){c -(}
.         svy: logit Suic i.St `model_eq', or 
{txt}(running {bf:logit} on estimation sample)
{res}
{txt}Survey: Logistic regression

{col 1}Number of strata{col 20}= {res}        1{txt}{col 47}Number of obs{col 65}= {res}  11,813,849
{txt}{col 1}Number of PSUs{col 20}= {res}      918{txt}{col 47}Population size{col 65}={res}  418,785,985
{txt}{col 47}Design df{col 65}= {res}         917
{txt}{col 47}F({res}  60{txt},{res}    858{txt}){col 65}= {res}      561.17
{txt}{col 47}Prob > F{col 65}= {res}      0.0000

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}  Linearized
{col 1}        Suic{col 14}{c |} Odds Ratio{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}St {c |}
{space 10}8  {c |}{col 14}{res}{space 2} .9712405{col 26}{space 2}  .080132{col 37}{space 1}   -0.35{col 46}{space 3}0.724{col 54}{space 4}  .826049{col 67}{space 3} 1.141952
{txt}{space 9}13  {c |}{col 14}{res}{space 2} .6994752{col 26}{space 2}  .060445{col 37}{space 1}   -4.14{col 46}{space 3}0.000{col 54}{space 4} .5903624{col 67}{space 3} .8287545
{txt}{space 9}21  {c |}{col 14}{res}{space 2} .6145812{col 26}{space 2} .0522819{col 37}{space 1}   -5.72{col 46}{space 3}0.000{col 54}{space 4}  .520083{col 67}{space 3} .7262497
{txt}{space 9}24  {c |}{col 14}{res}{space 2} .5539578{col 26}{space 2} .0468949{col 37}{space 1}   -6.98{col 46}{space 3}0.000{col 54}{space 4} .4691627{col 67}{space 3} .6540783
{txt}{space 9}25  {c |}{col 14}{res}{space 2} .4286072{col 26}{space 2} .0362518{col 37}{space 1}  -10.02{col 46}{space 3}0.000{col 54}{space 4} .3630524{col 67}{space 3} .5059989
{txt}{space 9}34  {c |}{col 14}{res}{space 2} .4768168{col 26}{space 2} .0425556{col 37}{space 1}   -8.30{col 46}{space 3}0.000{col 54}{space 4} .4002045{col 67}{space 3} .5680951
{txt}{space 9}35  {c |}{col 14}{res}{space 2} .9794068{col 26}{space 2}  .096444{col 37}{space 1}   -0.21{col 46}{space 3}0.833{col 54}{space 4} .8072964{col 67}{space 3}  1.18821
{txt}{space 9}37  {c |}{col 14}{res}{space 2} .7243963{col 26}{space 2} .0652635{col 37}{space 1}   -3.58{col 46}{space 3}0.000{col 54}{space 4} .6069977{col 67}{space 3} .8645009
{txt}{space 9}40  {c |}{col 14}{res}{space 2} .5982952{col 26}{space 2} .0559406{col 37}{space 1}   -5.49{col 46}{space 3}0.000{col 54}{space 4} .4979928{col 67}{space 3} .7187999
{txt}{space 9}41  {c |}{col 14}{res}{space 2} .8231015{col 26}{space 2} .0670549{col 37}{space 1}   -2.39{col 46}{space 3}0.017{col 54}{space 4} .7014838{col 67}{space 3} .9658044
{txt}{space 9}44  {c |}{col 14}{res}{space 2} .4929869{col 26}{space 2} .0418237{col 37}{space 1}   -8.34{col 46}{space 3}0.000{col 54}{space 4} .4173747{col 67}{space 3}  .582297
{txt}{space 9}45  {c |}{col 14}{res}{space 2}  .634928{col 26}{space 2} .0561629{col 37}{space 1}   -5.14{col 46}{space 3}0.000{col 54}{space 4} .5337421{col 67}{space 3} .7552966
{txt}{space 9}49  {c |}{col 14}{res}{space 2} 1.860065{col 26}{space 2} .3171078{col 37}{space 1}    3.64{col 46}{space 3}0.000{col 54}{space 4} 1.331133{col 67}{space 3} 2.599169
{txt}{space 9}51  {c |}{col 14}{res}{space 2} .7623463{col 26}{space 2} .0630429{col 37}{space 1}   -3.28{col 46}{space 3}0.001{col 54}{space 4} .6481394{col 67}{space 3} .8966772
{txt}{space 9}55  {c |}{col 14}{res}{space 2} .5768447{col 26}{space 2} .0482479{col 37}{space 1}   -6.58{col 46}{space 3}0.000{col 54}{space 4}  .489519{col 67}{space 3} .6797486
{txt}{space 12} {c |}
{space 8}Year {c |}
{space 7}2006  {c |}{col 14}{res}{space 2} .9388219{col 26}{space 2} .0168145{col 37}{space 1}   -3.52{col 46}{space 3}0.000{col 54}{space 4} .9063958{col 67}{space 3} .9724081
{txt}{space 7}2007  {c |}{col 14}{res}{space 2} 1.009411{col 26}{space 2} .0185846{col 37}{space 1}    0.51{col 46}{space 3}0.611{col 54}{space 4} .9735893{col 67}{space 3} 1.046552
{txt}{space 7}2008  {c |}{col 14}{res}{space 2} 1.011119{col 26}{space 2} .0203077{col 37}{space 1}    0.55{col 46}{space 3}0.582{col 54}{space 4} .9720391{col 67}{space 3}  1.05177
{txt}{space 7}2009  {c |}{col 14}{res}{space 2}  1.05289{col 26}{space 2} .0209392{col 37}{space 1}    2.59{col 46}{space 3}0.010{col 54}{space 4} 1.012587{col 67}{space 3} 1.094797
{txt}{space 7}2010  {c |}{col 14}{res}{space 2} 1.053775{col 26}{space 2} .0220449{col 37}{space 1}    2.50{col 46}{space 3}0.012{col 54}{space 4} 1.011387{col 67}{space 3}  1.09794
{txt}{space 7}2011  {c |}{col 14}{res}{space 2} 1.102921{col 26}{space 2} .0243355{col 37}{space 1}    4.44{col 46}{space 3}0.000{col 54}{space 4} 1.056181{col 67}{space 3}  1.15173
{txt}{space 12} {c |}
{space 4}1.Female {c |}{col 14}{res}{space 2} .2490982{col 26}{space 2} .0039297{col 37}{space 1}  -88.10{col 46}{space 3}0.000{col 54}{space 4} .2415042{col 67}{space 3} .2569311
{txt}std_same_p~x {c |}{col 14}{res}{space 2} 1.005328{col 26}{space 2} .0143733{col 37}{space 1}    0.37{col 46}{space 3}0.710{col 54}{space 4} .9775119{col 67}{space 3} 1.033936
{txt}{space 12} {c |}
{space 6}Female#{c |}
{space 10}c. {c |}
std_same_p~x {c |}
{space 10}1  {c |}{col 14}{res}{space 2} .9629966{col 26}{space 2} .0266111{col 37}{space 1}   -1.36{col 46}{space 3}0.173{col 54}{space 4} .9121618{col 67}{space 3} 1.016664
{txt}{space 12} {c |}
{space 5}AgeGrp4 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} 2.226426{col 26}{space 2} .0467057{col 37}{space 1}   38.15{col 46}{space 3}0.000{col 54}{space 4} 2.136624{col 67}{space 3} 2.320001
{txt}{space 10}3  {c |}{col 14}{res}{space 2} 2.434828{col 26}{space 2} .0610908{col 37}{space 1}   35.47{col 46}{space 3}0.000{col 54}{space 4} 2.317838{col 67}{space 3} 2.557723
{txt}{space 10}4  {c |}{col 14}{res}{space 2} 2.012544{col 26}{space 2} .0552589{col 37}{space 1}   25.47{col 46}{space 3}0.000{col 54}{space 4} 1.906966{col 67}{space 3} 2.123968
{txt}{space 12} {c |}
std_same_p~4 {c |}{col 14}{res}{space 2} .9649612{col 26}{space 2}  .017637{col 37}{space 1}   -1.95{col 46}{space 3}0.051{col 54}{space 4} .9309611{col 67}{space 3} 1.000203
{txt}{space 12} {c |}
{space 5}AgeGrp4#{c |}
{space 10}c. {c |}
std_same_p~4 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .9534748{col 26}{space 2} .0193684{col 37}{space 1}   -2.35{col 46}{space 3}0.019{col 54}{space 4} .9162109{col 67}{space 3} .9922542
{txt}{space 10}3  {c |}{col 14}{res}{space 2} 1.029345{col 26}{space 2} .0224854{col 37}{space 1}    1.32{col 46}{space 3}0.186{col 54}{space 4} .9861484{col 67}{space 3} 1.074433
{txt}{space 10}4  {c |}{col 14}{res}{space 2} 1.069211{col 26}{space 2} .0276634{col 37}{space 1}    2.59{col 46}{space 3}0.010{col 54}{space 4} 1.016275{col 67}{space 3} 1.124904
{txt}{space 12} {c |}
{space 7}Race5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2}  .394852{col 26}{space 2} .0130966{col 37}{space 1}  -28.02{col 46}{space 3}0.000{col 54}{space 4}  .369968{col 67}{space 3} .4214098
{txt}{space 10}3  {c |}{col 14}{res}{space 2} .9060984{col 26}{space 2} .0703863{col 37}{space 1}   -1.27{col 46}{space 3}0.205{col 54}{space 4} .7779759{col 67}{space 3} 1.055321
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .5660694{col 26}{space 2} .0325357{col 37}{space 1}   -9.90{col 46}{space 3}0.000{col 54}{space 4} .5056859{col 67}{space 3} .6336632
{txt}{space 10}5  {c |}{col 14}{res}{space 2} .4549554{col 26}{space 2} .0205378{col 37}{space 1}  -17.45{col 46}{space 3}0.000{col 54}{space 4} .4163827{col 67}{space 3} .4971013
{txt}{space 12} {c |}
std_same_~e5 {c |}{col 14}{res}{space 2} .9655901{col 26}{space 2} .0144024{col 37}{space 1}   -2.35{col 46}{space 3}0.019{col 54}{space 4} .9377342{col 67}{space 3} .9942734
{txt}{space 12} {c |}
{space 7}Race5#{c |}
{space 10}c. {c |}
std_same_~e5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .9791058{col 26}{space 2} .0325337{col 37}{space 1}   -0.64{col 46}{space 3}0.525{col 54}{space 4} .9172941{col 67}{space 3} 1.045083
{txt}{space 10}3  {c |}{col 14}{res}{space 2} 1.118089{col 26}{space 2} .0579571{col 37}{space 1}    2.15{col 46}{space 3}0.032{col 54}{space 4} 1.009939{col 67}{space 3}  1.23782
{txt}{space 10}4  {c |}{col 14}{res}{space 2} 1.103079{col 26}{space 2} .0246603{col 37}{space 1}    4.39{col 46}{space 3}0.000{col 54}{space 4} 1.055728{col 67}{space 3} 1.152553
{txt}{space 10}5  {c |}{col 14}{res}{space 2} 1.121464{col 26}{space 2} .0288546{col 37}{space 1}    4.46{col 46}{space 3}0.000{col 54}{space 4} 1.066241{col 67}{space 3} 1.179547
{txt}{space 12} {c |}
{space 3}1.BornUSA {c |}{col 14}{res}{space 2} 1.582218{col 26}{space 2} .0650482{col 37}{space 1}   11.16{col 46}{space 3}0.000{col 54}{space 4} 1.459571{col 67}{space 3}  1.71517
{txt}std_same_p~A {c |}{col 14}{res}{space 2} .9586269{col 26}{space 2} .0168599{col 37}{space 1}   -2.40{col 46}{space 3}0.016{col 54}{space 4} .9261029{col 67}{space 3}  .992293
{txt}{space 12} {c |}
{space 5}BornUSA#{c |}
{space 10}c. {c |}
std_same_p~A {c |}
{space 10}1  {c |}{col 14}{res}{space 2} 1.095356{col 26}{space 2}   .02372{col 37}{space 1}    4.21{col 46}{space 3}0.000{col 54}{space 4} 1.049779{col 67}{space 3} 1.142911
{txt}{space 12} {c |}
{space 4}MarStat5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} 2.252674{col 26}{space 2} .0534644{col 37}{space 1}   34.22{col 46}{space 3}0.000{col 54}{space 4} 2.150154{col 67}{space 3} 2.360083
{txt}{space 10}3  {c |}{col 14}{res}{space 2} 3.107265{col 26}{space 2} .0441949{col 37}{space 1}   79.71{col 46}{space 3}0.000{col 54}{space 4}  3.02173{col 67}{space 3} 3.195222
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .9368733{col 26}{space 2} .0852547{col 37}{space 1}   -0.72{col 46}{space 3}0.474{col 54}{space 4} .7836458{col 67}{space 3} 1.120062
{txt}{space 10}5  {c |}{col 14}{res}{space 2} 2.220797{col 26}{space 2}  .038923{col 37}{space 1}   45.52{col 46}{space 3}0.000{col 54}{space 4} 2.145707{col 67}{space 3} 2.298514
{txt}{space 12} {c |}
std_same_~t5 {c |}{col 14}{res}{space 2} .9406041{col 26}{space 2}  .011226{col 37}{space 1}   -5.13{col 46}{space 3}0.000{col 54}{space 4} .9188286{col 67}{space 3} .9628957
{txt}{space 12} {c |}
{space 4}MarStat5#{c |}
{space 10}c. {c |}
std_same_~t5 {c |}
{space 10}2  {c |}{col 14}{res}{space 2} .9984545{col 26}{space 2} .0258072{col 37}{space 1}   -0.06{col 46}{space 3}0.952{col 54}{space 4} .9490696{col 67}{space 3} 1.050409
{txt}{space 10}3  {c |}{col 14}{res}{space 2} 1.052445{col 26}{space 2} .0181783{col 37}{space 1}    2.96{col 46}{space 3}0.003{col 54}{space 4} 1.017367{col 67}{space 3} 1.088733
{txt}{space 10}4  {c |}{col 14}{res}{space 2} .9942609{col 26}{space 2} .0761519{col 37}{space 1}   -0.08{col 46}{space 3}0.940{col 54}{space 4} .8554989{col 67}{space 3}  1.15553
{txt}{space 10}5  {c |}{col 14}{res}{space 2} 1.098183{col 26}{space 2} .0194663{col 37}{space 1}    5.28{col 46}{space 3}0.000{col 54}{space 4} 1.060636{col 67}{space 3} 1.137059
{txt}{space 12} {c |}
{space 1}Rat_Poverty {c |}{col 14}{res}{space 2} .9975933{col 26}{space 2} .0019174{col 37}{space 1}   -1.25{col 46}{space 3}0.210{col 54}{space 4} .9938374{col 67}{space 3} 1.001363
{txt}{space 1}Rat_Mig_Cum {c |}{col 14}{res}{space 2} .1678542{col 26}{space 2}  .087636{col 37}{space 1}   -3.42{col 46}{space 3}0.001{col 54}{space 4} .0602471{col 67}{space 3} .4676581
{txt}{space 5}Pop_Den {c |}{col 14}{res}{space 2} 1.000002{col 26}{space 2} 5.95e-06{col 37}{space 1}    0.29{col 46}{space 3}0.769{col 54}{space 4} .9999901{col 67}{space 3} 1.000013
{txt}{space 1}Rat_GC_ProE {c |}{col 14}{res}{space 2} 1.000017{col 26}{space 2} 9.01e-06{col 37}{space 1}    1.83{col 46}{space 3}0.067{col 54}{space 4} .9999988{col 67}{space 3} 1.000034
{txt}{space 1}Rat_GC_ProM {c |}{col 14}{res}{space 2}  .999995{col 26}{space 2} .0000114{col 37}{space 1}   -0.44{col 46}{space 3}0.660{col 54}{space 4} .9999727{col 67}{space 3} 1.000017
{txt}{space 1}Rat_GC_ProB {c |}{col 14}{res}{space 2} .9998907{col 26}{space 2} .0000452{col 37}{space 1}   -2.42{col 46}{space 3}0.016{col 54}{space 4} .9998019{col 67}{space 3} .9999794
{txt}{space 2}Rat_GC_Jew {c |}{col 14}{res}{space 2} 1.000065{col 26}{space 2} .0000714{col 37}{space 1}    0.91{col 46}{space 3}0.363{col 54}{space 4} .9999249{col 67}{space 3} 1.000205
{txt}{space 2}Rat_GC_Oth {c |}{col 14}{res}{space 2} .9999067{col 26}{space 2} .0000246{col 37}{space 1}   -3.80{col 46}{space 3}0.000{col 54}{space 4} .9998585{col 67}{space 3} .9999549
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .000107{col 26}{space 2} .0000106{col 37}{space 1}  -92.05{col 46}{space 3}0.000{col 54}{space 4}  .000088{col 67}{space 3}   .00013
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline odds{txt}.{p_end}
{com}.         estimates store m1 
. 
.         if (`model_version' <= 4){c -(}
.                 mchange `margin_demographics', amount(all) delta(100) statistics(all) decimals(7)
.         {c )-}
. 
. {c )-}
{txt}
{com}. 
. if (`model_version' == 5 | `model_version' == 6) {c -(}
.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_Sex Female 5 `model'

                      {txt}std_same_prop_Sex
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.198216      -3.651791
{txt} 5%    {res}-1.338897      -3.651791
{txt}10%    {res}-.9757933      -3.651791       {txt}Obs         {res} 12,325,703
{txt}25%    {res}-.5328037      -3.651791       {txt}Sum of Wgt. {res}   12325703

{txt}50%    {res} .0197431                      {txt}Mean          {res} .0277567
                        {txt}Largest       Std. Dev.     {res} .9170927
{txt}75%    {res}  .572771       3.651791
{txt}90%    {res} 1.042457       3.651791       {txt}Variance      {res}  .841059
{txt}95%    {res} 1.417636       3.651791       {txt}Skewness      {res}  .036642
{txt}99%    {res} 2.199479       3.651791       {txt}Kurtosis      {res} 5.728495

{txt}Predictive margins

{col 1}Number of strata{col 20}= {res}        1{txt}{col 47}Number of obs{col 65}= {res}  11,763,920
{txt}{col 1}Number of PSUs{col 20}= {res}      918{txt}{col 47}Population size{col 65}={res}  418,785,985
{txt}{col 47}Subpop. no. obs{col 65}={res}   11,078,807
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 1}Model VCE{col 14}: {res}Linearized{txt}{col 47}Design df{col 65}= {res}         917

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(Suic), predict(pr)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 2}-3.651791}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 2}-2.191074}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 2}-.7303581}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 3}.7303581}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 3}2.191074}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_p~x}{space 4}{txt:=} {space 3}3.651791}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}_at#Female {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .0002403{col 26}{space 2} .0000119{col 37}{space 1}   20.21{col 46}{space 3}0.000{col 54}{space 4} .0002169{col 67}{space 3} .0002636
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .0000687{col 26}{space 2} 4.99e-06{col 37}{space 1}   13.77{col 46}{space 3}0.000{col 54}{space 4} .0000589{col 67}{space 3} .0000785
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .0002421{col 26}{space 2} 7.05e-06{col 37}{space 1}   34.36{col 46}{space 3}0.000{col 54}{space 4} .0002283{col 67}{space 3}  .000256
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0000655{col 26}{space 2} 3.08e-06{col 37}{space 1}   21.30{col 46}{space 3}0.000{col 54}{space 4} .0000595{col 67}{space 3} .0000716
{txt}{space 8}3 0  {c |}{col 14}{res}{space 2}  .000244{col 26}{space 2} 2.65e-06{col 37}{space 1}   92.08{col 46}{space 3}0.000{col 54}{space 4} .0002388{col 67}{space 3} .0002492
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} .0000625{col 26}{space 2} 1.43e-06{col 37}{space 1}   43.86{col 46}{space 3}0.000{col 54}{space 4} .0000597{col 67}{space 3} .0000653
{txt}{space 8}4 0  {c |}{col 14}{res}{space 2} .0002459{col 26}{space 2} 3.97e-06{col 37}{space 1}   61.96{col 46}{space 3}0.000{col 54}{space 4} .0002381{col 67}{space 3} .0002537
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0000596{col 26}{space 2} 8.79e-07{col 37}{space 1}   67.79{col 46}{space 3}0.000{col 54}{space 4} .0000579{col 67}{space 3} .0000613
{txt}{space 8}5 0  {c |}{col 14}{res}{space 2} .0002479{col 26}{space 2} 8.85e-06{col 37}{space 1}   28.01{col 46}{space 3}0.000{col 54}{space 4} .0002305{col 67}{space 3} .0002652
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} .0000569{col 26}{space 2} 2.05e-06{col 37}{space 1}   27.76{col 46}{space 3}0.000{col 54}{space 4} .0000528{col 67}{space 3} .0000609
{txt}{space 8}6 0  {c |}{col 14}{res}{space 2} .0002498{col 26}{space 2}  .000014{col 37}{space 1}   17.79{col 46}{space 3}0.000{col 54}{space 4} .0002222{col 67}{space 3} .0002773
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0000542{col 26}{space 2} 3.33e-06{col 37}{space 1}   16.31{col 46}{space 3}0.000{col 54}{space 4} .0000477{col 67}{space 3} .0000608
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_AgeGrp4 AgeGrp4 5 `model'

                    {txt}std_same_prop_AgeGrp4
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.616519      -5.047376
{txt} 5%    {res}-1.386563      -5.047376
{txt}10%    {res}-1.060889      -5.047376       {txt}Obs         {res} 12,325,703
{txt}25%    {res}-.4953907      -5.047376       {txt}Sum of Wgt. {res}   12325703

{txt}50%    {res} .0626631                      {txt}Mean          {res} .1298547
                        {txt}Largest       Std. Dev.     {res} 1.066722
{txt}75%    {res} .6755717       5.422427
{txt}90%    {res} 1.363808       5.422427       {txt}Variance      {res} 1.137896
{txt}95%    {res} 1.896452       5.422427       {txt}Skewness      {res}  .405324
{txt}99%    {res} 3.088452       5.422427       {txt}Kurtosis      {res}  5.40646

{txt}Predictive margins

{col 1}Number of strata{col 20}= {res}        1{txt}{col 47}Number of obs{col 65}= {res}  11,763,920
{txt}{col 1}Number of PSUs{col 20}= {res}      918{txt}{col 47}Population size{col 65}={res}  418,785,985
{txt}{col 47}Subpop. no. obs{col 65}={res}   11,078,807
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 1}Model VCE{col 14}: {res}Linearized{txt}{col 47}Design df{col 65}= {res}         917

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(Suic), predict(pr)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 2}-5.047376}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 2}-2.953415}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 2}-.8594548}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 3}1.234506}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 3}3.328466}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_p~4}{space 4}{txt:=} {space 3}5.422427}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}_at#AgeGrp4 {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0000917{col 26}{space 2} 8.58e-06{col 37}{space 1}   10.69{col 46}{space 3}0.000{col 54}{space 4} .0000749{col 67}{space 3} .0001085
{txt}{space 8}1 2  {c |}{col 14}{res}{space 2} .0002596{col 26}{space 2} .0000126{col 37}{space 1}   20.59{col 46}{space 3}0.000{col 54}{space 4} .0002348{col 67}{space 3} .0002843
{txt}{space 8}1 3  {c |}{col 14}{res}{space 2} .0001929{col 26}{space 2} 8.88e-06{col 37}{space 1}   21.73{col 46}{space 3}0.000{col 54}{space 4} .0001755{col 67}{space 3} .0002103
{txt}{space 8}1 4  {c |}{col 14}{res}{space 2} .0001316{col 26}{space 2}  .000011{col 37}{space 1}   11.96{col 46}{space 3}0.000{col 54}{space 4}   .00011{col 67}{space 3} .0001532
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0000851{col 26}{space 2} 4.84e-06{col 37}{space 1}   17.58{col 46}{space 3}0.000{col 54}{space 4} .0000756{col 67}{space 3} .0000946
{txt}{space 8}2 2  {c |}{col 14}{res}{space 2}  .000218{col 26}{space 2} 6.74e-06{col 37}{space 1}   32.35{col 46}{space 3}0.000{col 54}{space 4} .0002048{col 67}{space 3} .0002313
{txt}{space 8}2 3  {c |}{col 14}{res}{space 2} .0001902{col 26}{space 2} 5.33e-06{col 37}{space 1}   35.67{col 46}{space 3}0.000{col 54}{space 4} .0001797{col 67}{space 3} .0002007
{txt}{space 8}2 4  {c |}{col 14}{res}{space 2} .0001405{col 26}{space 2} 6.83e-06{col 37}{space 1}   20.59{col 46}{space 3}0.000{col 54}{space 4} .0001271{col 67}{space 3} .0001539
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2}  .000079{col 26}{space 2} 2.00e-06{col 37}{space 1}   39.41{col 46}{space 3}0.000{col 54}{space 4}  .000075{col 67}{space 3} .0000829
{txt}{space 8}3 2  {c |}{col 14}{res}{space 2} .0001831{col 26}{space 2} 2.74e-06{col 37}{space 1}   66.80{col 46}{space 3}0.000{col 54}{space 4} .0001778{col 67}{space 3} .0001885
{txt}{space 8}3 3  {c |}{col 14}{res}{space 2} .0001875{col 26}{space 2} 2.43e-06{col 37}{space 1}   77.02{col 46}{space 3}0.000{col 54}{space 4} .0001828{col 67}{space 3} .0001923
{txt}{space 8}3 4  {c |}{col 14}{res}{space 2}   .00015{col 26}{space 2} 2.73e-06{col 37}{space 1}   54.98{col 46}{space 3}0.000{col 54}{space 4} .0001447{col 67}{space 3} .0001554
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0000733{col 26}{space 2} 2.30e-06{col 37}{space 1}   31.93{col 46}{space 3}0.000{col 54}{space 4} .0000688{col 67}{space 3} .0000778
{txt}{space 8}4 2  {c |}{col 14}{res}{space 2} .0001538{col 26}{space 2} 1.97e-06{col 37}{space 1}   77.98{col 46}{space 3}0.000{col 54}{space 4}   .00015{col 67}{space 3} .0001577
{txt}{space 8}4 3  {c |}{col 14}{res}{space 2} .0001849{col 26}{space 2} 3.01e-06{col 37}{space 1}   61.45{col 46}{space 3}0.000{col 54}{space 4}  .000179{col 67}{space 3} .0001908
{txt}{space 8}4 4  {c |}{col 14}{res}{space 2} .0001602{col 26}{space 2} 4.81e-06{col 37}{space 1}   33.33{col 46}{space 3}0.000{col 54}{space 4} .0001508{col 67}{space 3} .0001696
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2}  .000068{col 26}{space 2} 4.43e-06{col 37}{space 1}   15.34{col 46}{space 3}0.000{col 54}{space 4} .0000593{col 67}{space 3} .0000767
{txt}{space 8}5 2  {c |}{col 14}{res}{space 2} .0001292{col 26}{space 2} 3.60e-06{col 37}{space 1}   35.88{col 46}{space 3}0.000{col 54}{space 4} .0001222{col 67}{space 3} .0001363
{txt}{space 8}5 3  {c |}{col 14}{res}{space 2} .0001823{col 26}{space 2} 5.98e-06{col 37}{space 1}   30.50{col 46}{space 3}0.000{col 54}{space 4} .0001706{col 67}{space 3}  .000194
{txt}{space 8}5 4  {c |}{col 14}{res}{space 2}  .000171{col 26}{space 2} .0000109{col 37}{space 1}   15.68{col 46}{space 3}0.000{col 54}{space 4} .0001496{col 67}{space 3} .0001924
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0000631{col 26}{space 2} 6.45e-06{col 37}{space 1}    9.79{col 46}{space 3}0.000{col 54}{space 4} .0000505{col 67}{space 3} .0000758
{txt}{space 8}6 2  {c |}{col 14}{res}{space 2} .0001085{col 26}{space 2} 4.93e-06{col 37}{space 1}   22.02{col 46}{space 3}0.000{col 54}{space 4} .0000989{col 67}{space 3} .0001182
{txt}{space 8}6 3  {c |}{col 14}{res}{space 2} .0001798{col 26}{space 2} 9.16e-06{col 37}{space 1}   19.62{col 46}{space 3}0.000{col 54}{space 4} .0001618{col 67}{space 3} .0001977
{txt}{space 8}6 4  {c |}{col 14}{res}{space 2} .0001826{col 26}{space 2} .0000181{col 37}{space 1}   10.09{col 46}{space 3}0.000{col 54}{space 4}  .000147{col 67}{space 3} .0002181
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_Race5 Race5 5 `model'

                     {txt}std_same_prop_Race5
{hline 61}
      Percentiles      Smallest
 1%    {res} -2.38687      -3.559958
{txt} 5%    {res}-1.335796      -3.559958
{txt}10%    {res} -.954112      -3.559958       {txt}Obs         {res} 12,325,703
{txt}25%    {res}-.2537747      -3.559958       {txt}Sum of Wgt. {res}   12325703

{txt}50%    {res} .4283095                      {txt}Mean          {res} .4280245
                        {txt}Largest       Std. Dev.     {res} 1.247861
{txt}75%    {res} 1.022571       8.613633
{txt}90%    {res} 1.233253       8.613633       {txt}Variance      {res} 1.557157
{txt}95%    {res} 2.080373       8.613633       {txt}Skewness      {res} 1.751577
{txt}99%    {res} 6.650221       8.613633       {txt}Kurtosis      {res} 11.82055

{txt}Predictive margins

{col 1}Number of strata{col 20}= {res}        1{txt}{col 47}Number of obs{col 65}= {res}  11,763,920
{txt}{col 1}Number of PSUs{col 20}= {res}      918{txt}{col 47}Population size{col 65}={res}  418,785,985
{txt}{col 47}Subpop. no. obs{col 65}={res}   11,078,807
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 1}Model VCE{col 14}: {res}Linearized{txt}{col 47}Design df{col 65}= {res}         917

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(Suic), predict(pr)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 2}-3.559958}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}-1.12524}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}1.309478}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}3.744196}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}6.178914}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_~e5}{space 4}{txt:=} {space 3}8.613633}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}_at#Race5 {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0001931{col 26}{space 2} 9.92e-06{col 37}{space 1}   19.47{col 46}{space 3}0.000{col 54}{space 4} .0001736{col 67}{space 3} .0002125
{txt}{space 8}1 2  {c |}{col 14}{res}{space 2} .0000822{col 26}{space 2} 9.49e-06{col 37}{space 1}    8.67{col 46}{space 3}0.000{col 54}{space 4} .0000636{col 67}{space 3} .0001008
{txt}{space 8}1 3  {c |}{col 14}{res}{space 2} .0001176{col 26}{space 2} .0000258{col 37}{space 1}    4.56{col 46}{space 3}0.000{col 54}{space 4}  .000067{col 67}{space 3} .0001682
{txt}{space 8}1 4  {c |}{col 14}{res}{space 2} .0000771{col 26}{space 2} 8.08e-06{col 37}{space 1}    9.54{col 46}{space 3}0.000{col 54}{space 4} .0000612{col 67}{space 3}  .000093
{txt}{space 8}1 5  {c |}{col 14}{res}{space 2} .0000584{col 26}{space 2} 6.33e-06{col 37}{space 1}    9.23{col 46}{space 3}0.000{col 54}{space 4}  .000046{col 67}{space 3} .0000708
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0001773{col 26}{space 2} 2.91e-06{col 37}{space 1}   60.91{col 46}{space 3}0.000{col 54}{space 4} .0001716{col 67}{space 3}  .000183
{txt}{space 8}2 2  {c |}{col 14}{res}{space 2} .0000717{col 26}{space 2} 3.95e-06{col 37}{space 1}   18.16{col 46}{space 3}0.000{col 54}{space 4}  .000064{col 67}{space 3} .0000795
{txt}{space 8}2 3  {c |}{col 14}{res}{space 2} .0001417{col 26}{space 2} .0000162{col 37}{space 1}    8.77{col 46}{space 3}0.000{col 54}{space 4}   .00011{col 67}{space 3} .0001734
{txt}{space 8}2 4  {c |}{col 14}{res}{space 2} .0000899{col 26}{space 2} 6.41e-06{col 37}{space 1}   14.03{col 46}{space 3}0.000{col 54}{space 4} .0000773{col 67}{space 3} .0001025
{txt}{space 8}2 5  {c |}{col 14}{res}{space 2} .0000709{col 26}{space 2} 4.40e-06{col 37}{space 1}   16.11{col 46}{space 3}0.000{col 54}{space 4} .0000623{col 67}{space 3} .0000796
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2} .0001628{col 26}{space 2} 3.77e-06{col 37}{space 1}   43.16{col 46}{space 3}0.000{col 54}{space 4} .0001554{col 67}{space 3} .0001702
{txt}{space 8}3 2  {c |}{col 14}{res}{space 2} .0000626{col 26}{space 2} 1.80e-06{col 37}{space 1}   34.65{col 46}{space 3}0.000{col 54}{space 4}  .000059{col 67}{space 3} .0000661
{txt}{space 8}3 3  {c |}{col 14}{res}{space 2} .0001708{col 26}{space 2} .0000123{col 37}{space 1}   13.85{col 46}{space 3}0.000{col 54}{space 4} .0001466{col 67}{space 3} .0001949
{txt}{space 8}3 4  {c |}{col 14}{res}{space 2} .0001048{col 26}{space 2} 4.67e-06{col 37}{space 1}   22.43{col 46}{space 3}0.000{col 54}{space 4} .0000956{col 67}{space 3}  .000114
{txt}{space 8}3 5  {c |}{col 14}{res}{space 2} .0000861{col 26}{space 2} 3.03e-06{col 37}{space 1}   28.37{col 46}{space 3}0.000{col 54}{space 4} .0000801{col 67}{space 3}  .000092
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0001495{col 26}{space 2} 8.77e-06{col 37}{space 1}   17.05{col 46}{space 3}0.000{col 54}{space 4} .0001323{col 67}{space 3} .0001667
{txt}{space 8}4 2  {c |}{col 14}{res}{space 2} .0000546{col 26}{space 2} 4.47e-06{col 37}{space 1}   12.20{col 46}{space 3}0.000{col 54}{space 4} .0000458{col 67}{space 3} .0000633
{txt}{space 8}4 3  {c |}{col 14}{res}{space 2} .0002058{col 26}{space 2} .0000323{col 37}{space 1}    6.37{col 46}{space 3}0.000{col 54}{space 4} .0001424{col 67}{space 3} .0002691
{txt}{space 8}4 4  {c |}{col 14}{res}{space 2} .0001222{col 26}{space 2} 5.05e-06{col 37}{space 1}   24.21{col 46}{space 3}0.000{col 54}{space 4} .0001123{col 67}{space 3} .0001321
{txt}{space 8}4 5  {c |}{col 14}{res}{space 2} .0001045{col 26}{space 2} 6.52e-06{col 37}{space 1}   16.03{col 46}{space 3}0.000{col 54}{space 4} .0000917{col 67}{space 3} .0001173
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} .0001373{col 26}{space 2}  .000013{col 37}{space 1}   10.55{col 46}{space 3}0.000{col 54}{space 4} .0001118{col 67}{space 3} .0001628
{txt}{space 8}5 2  {c |}{col 14}{res}{space 2} .0000476{col 26}{space 2} 6.85e-06{col 37}{space 1}    6.95{col 46}{space 3}0.000{col 54}{space 4} .0000342{col 67}{space 3}  .000061
{txt}{space 8}5 3  {c |}{col 14}{res}{space 2} .0002479{col 26}{space 2} .0000662{col 37}{space 1}    3.75{col 46}{space 3}0.000{col 54}{space 4}  .000118{col 67}{space 3} .0003778
{txt}{space 8}5 4  {c |}{col 14}{res}{space 2} .0001425{col 26}{space 2} 9.27e-06{col 37}{space 1}   15.36{col 46}{space 3}0.000{col 54}{space 4} .0001243{col 67}{space 3} .0001607
{txt}{space 8}5 5  {c |}{col 14}{res}{space 2} .0001268{col 26}{space 2} .0000138{col 37}{space 1}    9.20{col 46}{space 3}0.000{col 54}{space 4} .0000998{col 67}{space 3} .0001539
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0001261{col 26}{space 2} .0000165{col 37}{space 1}    7.63{col 46}{space 3}0.000{col 54}{space 4} .0000937{col 67}{space 3} .0001585
{txt}{space 8}6 2  {c |}{col 14}{res}{space 2} .0000415{col 26}{space 2} 8.58e-06{col 37}{space 1}    4.84{col 46}{space 3}0.000{col 54}{space 4} .0000247{col 67}{space 3} .0000584
{txt}{space 8}6 3  {c |}{col 14}{res}{space 2} .0002987{col 26}{space 2} .0001138{col 37}{space 1}    2.62{col 46}{space 3}0.009{col 54}{space 4} .0000754{col 67}{space 3} .0005221
{txt}{space 8}6 4  {c |}{col 14}{res}{space 2} .0001662{col 26}{space 2} .0000163{col 37}{space 1}   10.22{col 46}{space 3}0.000{col 54}{space 4} .0001342{col 67}{space 3} .0001981
{txt}{space 8}6 5  {c |}{col 14}{res}{space 2}  .000154{col 26}{space 2} .0000243{col 37}{space 1}    6.33{col 46}{space 3}0.000{col 54}{space 4} .0001062{col 67}{space 3} .0002017
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_BornUSA BornUSA 5 `model'

                    {txt}std_same_prop_BornUSA
{hline 61}
      Percentiles      Smallest
 1%    {res}-5.212165      -7.767567
{txt} 5%    {res}-2.741793      -7.767567
{txt}10%    {res}-1.727814      -7.767567       {txt}Obs         {res} 12,325,703
{txt}25%    {res}-.5312092      -7.767567       {txt}Sum of Wgt. {res}   12325703

{txt}50%    {res} .1453823                      {txt}Mean          {res}-.1121698
                        {txt}Largest       Std. Dev.     {res} 1.410662
{txt}75%    {res} .6559842       7.767567
{txt}90%    {res} .8395722       7.767567       {txt}Variance      {res} 1.989967
{txt}95%    {res}  .913883       7.767567       {txt}Skewness      {res} -.743237
{txt}99%    {res} 4.551424       7.767567       {txt}Kurtosis      {res} 8.949475

{txt}Predictive margins

{col 1}Number of strata{col 20}= {res}        1{txt}{col 47}Number of obs{col 65}= {res}  11,763,920
{txt}{col 1}Number of PSUs{col 20}= {res}      918{txt}{col 47}Population size{col 65}={res}  418,785,985
{txt}{col 47}Subpop. no. obs{col 65}={res}   11,078,807
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 1}Model VCE{col 14}: {res}Linearized{txt}{col 47}Design df{col 65}= {res}         917

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(Suic), predict(pr)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 2}-7.767567}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 3}-4.66054}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 2}-1.553513}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 3}1.553513}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 4}4.66054}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_p~A}{space 4}{txt:=} {space 3}7.767567}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}_at#BornUSA {c |}
{space 8}1 0  {c |}{col 14}{res}{space 2} .0001392{col 26}{space 2} .0000231{col 37}{space 1}    6.03{col 46}{space 3}0.000{col 54}{space 4} .0000939{col 67}{space 3} .0001845
{txt}{space 8}1 1  {c |}{col 14}{res}{space 2} .0001086{col 26}{space 2} 7.00e-06{col 37}{space 1}   15.50{col 46}{space 3}0.000{col 54}{space 4} .0000948{col 67}{space 3} .0001223
{txt}{space 8}2 0  {c |}{col 14}{res}{space 2} .0001221{col 26}{space 2} .0000137{col 37}{space 1}    8.89{col 46}{space 3}0.000{col 54}{space 4} .0000951{col 67}{space 3}  .000149
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0001263{col 26}{space 2} 4.61e-06{col 37}{space 1}   27.41{col 46}{space 3}0.000{col 54}{space 4} .0001173{col 67}{space 3} .0001354
{txt}{space 8}3 0  {c |}{col 14}{res}{space 2}  .000107{col 26}{space 2} 6.56e-06{col 37}{space 1}   16.33{col 46}{space 3}0.000{col 54}{space 4} .0000942{col 67}{space 3} .0001199
{txt}{space 8}3 1  {c |}{col 14}{res}{space 2}  .000147{col 26}{space 2} 1.58e-06{col 37}{space 1}   93.15{col 46}{space 3}0.000{col 54}{space 4} .0001439{col 67}{space 3} .0001501
{txt}{space 8}4 0  {c |}{col 14}{res}{space 2} .0000939{col 26}{space 2} 2.70e-06{col 37}{space 1}   34.74{col 46}{space 3}0.000{col 54}{space 4} .0000886{col 67}{space 3} .0000992
{txt}{space 8}4 1  {c |}{col 14}{res}{space 2} .0001711{col 26}{space 2} 3.89e-06{col 37}{space 1}   43.96{col 46}{space 3}0.000{col 54}{space 4} .0001635{col 67}{space 3} .0001787
{txt}{space 8}5 0  {c |}{col 14}{res}{space 2} .0000823{col 26}{space 2} 5.13e-06{col 37}{space 1}   16.06{col 46}{space 3}0.000{col 54}{space 4} .0000723{col 67}{space 3} .0000924
{txt}{space 8}5 1  {c |}{col 14}{res}{space 2} .0001991{col 26}{space 2}   .00001{col 37}{space 1}   19.85{col 46}{space 3}0.000{col 54}{space 4} .0001794{col 67}{space 3} .0002188
{txt}{space 8}6 0  {c |}{col 14}{res}{space 2} .0000722{col 26}{space 2} 8.20e-06{col 37}{space 1}    8.81{col 46}{space 3}0.000{col 54}{space 4} .0000561{col 67}{space 3} .0000883
{txt}{space 8}6 1  {c |}{col 14}{res}{space 2} .0002317{col 26}{space 2} .0000182{col 37}{space 1}   12.73{col 46}{space 3}0.000{col 54}{space 4}  .000196{col 67}{space 3} .0002674
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}.         estimates restore m1
{txt}(results {stata estimates replay m1:m1} are active now)
{com}.         margin_interact std_same_prop_MarStat5 MarStat5 5 `model'

                   {txt}std_same_prop_MarStat5
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.414584      -4.713632
{txt} 5%    {res}-1.571053      -4.713632
{txt}10%    {res}-1.259019      -4.713632       {txt}Obs         {res} 12,325,242
{txt}25%    {res}-.5265412      -4.713632       {txt}Sum of Wgt. {res}   12325242

{txt}50%    {res} .1617559                      {txt}Mean          {res} .1414067
                        {txt}Largest       Std. Dev.     {res} 1.067954
{txt}75%    {res} .8204068       5.008139
{txt}90%    {res} 1.396341       5.008139       {txt}Variance      {res} 1.140527
{txt}95%    {res} 1.714077       5.008139       {txt}Skewness      {res}-.0465515
{txt}99%    {res} 2.728096       5.008139       {txt}Kurtosis      {res} 4.792867

{txt}Predictive margins

{col 1}Number of strata{col 20}= {res}        1{txt}{col 47}Number of obs{col 65}= {res}  11,763,920
{txt}{col 1}Number of PSUs{col 20}= {res}      918{txt}{col 47}Population size{col 65}={res}  418,785,985
{txt}{col 47}Subpop. no. obs{col 65}={res}   11,078,807
{txt}{col 47}Subpop. size{col 65}={res}            .
{txt}{col 1}Model VCE{col 14}: {res}Linearized{txt}{col 47}Design df{col 65}= {res}         917

{txt}{p2colset 1 14 16 2}{...}
{p2col:Expression}:{space 1}{res:Pr(Suic), predict(pr)}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:1._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 2}-4.713632}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:2._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 2}-2.769278}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:3._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 2}-.8249235}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:4._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 3}1.119431}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:5._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 3}3.063785}{p_end}
{p2colreset}{...}

{txt}{p2colset 1 14 16 2}{...}
{p2col:6._at}:{space 1}{res:{txt:std_same_~t5}{space 4}{txt:=} {space 3}5.008139}{p_end}
{p2colreset}{...}

{res}{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26} Delta-method
{col 14}{c |}     Margin{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
_at#MarStat5 {c |}
{space 8}1 1  {c |}{col 14}{res}{space 2} .0001242{col 26}{space 2} 6.99e-06{col 37}{space 1}   17.76{col 46}{space 3}0.000{col 54}{space 4} .0001105{col 67}{space 3} .0001379
{txt}{space 8}1 2  {c |}{col 14}{res}{space 2} .0002817{col 26}{space 2} .0000269{col 37}{space 1}   10.49{col 46}{space 3}0.000{col 54}{space 4}  .000229{col 67}{space 3} .0003344
{txt}{space 8}1 3  {c |}{col 14}{res}{space 2} .0003031{col 26}{space 2} .0000199{col 37}{space 1}   15.23{col 46}{space 3}0.000{col 54}{space 4} .0002641{col 67}{space 3} .0003422
{txt}{space 8}1 4  {c |}{col 14}{res}{space 2} .0001195{col 26}{space 2} .0000471{col 37}{space 1}    2.54{col 46}{space 3}0.011{col 54}{space 4} .0000271{col 67}{space 3}  .000212
{txt}{space 8}1 5  {c |}{col 14}{res}{space 2} .0001773{col 26}{space 2} 9.23e-06{col 37}{space 1}   19.21{col 46}{space 3}0.000{col 54}{space 4} .0001592{col 67}{space 3} .0001955
{txt}{space 8}2 1  {c |}{col 14}{res}{space 2} .0001102{col 26}{space 2} 3.74e-06{col 37}{space 1}   29.47{col 46}{space 3}0.000{col 54}{space 4} .0001029{col 67}{space 3} .0001176
{txt}{space 8}2 2  {c |}{col 14}{res}{space 2} .0002493{col 26}{space 2} .0000136{col 37}{space 1}   18.38{col 46}{space 3}0.000{col 54}{space 4} .0002227{col 67}{space 3}  .000276
{txt}{space 8}2 3  {c |}{col 14}{res}{space 2} .0002972{col 26}{space 2} .0000119{col 37}{space 1}   25.00{col 46}{space 3}0.000{col 54}{space 4} .0002739{col 67}{space 3} .0003206
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{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{com}. 
.         if (`model_version' == 6) {c -(}
.                 estimates restore m1
.                 margin_interact std_same_prop_UnEmpl UnEmpl 5 `model'
.                 estimates restore m1
.                 margin_interact std_same_prop_PhysProb PhysProb 5 `model'
.         {c )-}
. 
. {c )-}
{txt}
{com}. 
. 
. log close 
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/N/project/suicide_study/pnas_replication/results/log/logit_5.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}18 Aug 2020, 09:56:52
{txt}{.-}
{smcl}
{txt}{sf}{ul off}